R Notebook

df <- read.delim("data/GP_metadata.txt")

df <- df %>%
  mutate(
    lat = as.numeric(sub(",.*", "", Lat_long)),
    long = as.numeric(sub(".*,", "", Lat_long))
  ) %>%
  filter(!is.na(lat), !is.na(long))


points_sf <- st_as_sf(df, coords = c("long", "lat"), crs = 4326)

hull <- st_convex_hull(st_union(points_sf))

uk <- ne_countries(scale = "medium", returnclass = "sf") %>% 
  filter(admin == "United Kingdom")

map_plot <- ggplot() +
  geom_sf(data = uk, fill = "gray95", color = "black") +
  geom_sf(data = hull, fill = "deepskyblue4", alpha = 0.4, color = "black") +
  theme_minimal() +
  coord_sf(expand = FALSE) 

ggsave("images/map_plot.png", map_plot, width = 6, height = 8, dpi = 300)

library(ggplot2)
library(plotly)
library(dplyr)

df_ancom <- read.delim("data/ITS/Taxonomy/Taxonomic_Abundance/F03_Establishment_ancom/data/ancom.tsv")
df_data <- read.delim("data/ITS/Taxonomy/Taxonomic_Abundance/F03_Establishment_ancom/data/data.tsv")

df_data$X <- df_data$id
df_data <- df_data[, -1]
df <- left_join(df_ancom, df_data)

p <- ggplot(df, aes(x = clr, y = W, text = X)) +
  geom_point(aes(color = `Reject.null.hypothesis`)) +
  scale_color_manual(values = c("grey", "cyan3")) +
  theme_minimal() +
  labs(x = "Centered Logarithmic (clr)",
       y = "W statistic",
       title = "Volcano plot (ANCOM results)") +
  theme(axis.text.x = element_blank(),
        axis.ticks.x = element_blank())

ggplotly(p, tooltip = "text")

library(readr)
library(dplyr)
library(tidyr)
library(leaflet)

Avis : le package ‘leaflet’ a été compilé avec la version R 4.4.3

df <- read.delim("data/16S/Beta_Diversity/bray_permanova_Year_group/data/raw_data.tsv")
df <- df[df$Group1 != "unknown" & df$Group2 != "unknown", ]



df_nat <- df %>%
  filter(Group1 == "1940-60" | Group2 == "1940-60") %>%
  mutate(
    Compared_to = ifelse(Group1 == "1940-60", Group2, Group1),
    Compared_to = factor(Compared_to, levels = c("1940-60", "1981-2000","2001-2010", "2011-2020"))
  )

plot1 <- ggplot(df_nat, aes(x = Compared_to, y = Distance, fill = Compared_to)) +
  geom_boxplot() +
  scale_fill_manual(values = c(
    "1940-60" = "#C6DBEF", 
    "1981-2000" = "#08519C", 
    "2001-2010" = "#3182BD",
    "2011-2020" = "skyblue"
  )) +
  theme_minimal() +
  labs(
    title = "Distance to group 1940-60",
    x = NULL,
    y = "Bray-Curtis Distance"
  ) +
  theme(
    axis.text.x = element_text(angle = 45, hjust = 1),
    legend.position = "none"
  )

df_seed <- df %>%
  filter(Group1 == "1981-2000" | Group2 == "1981-2000") %>%
  mutate(
    Compared_to = ifelse(Group1 == "1981-2000", Group2, Group1),
    Compared_to = factor(Compared_to, levels = c("1981-2000", "1940-60", "2001-2010","2011-2020"))
  )

plot2 <- ggplot(df_seed, aes(x = Compared_to, y = Distance, fill = Compared_to)) +
  geom_boxplot() +
  scale_fill_manual(values = c(
    "1940-60" = "#C6DBEF", 
    "1981-2000" = "#08519C", 
    "2001-2010" = "#3182BD",
    "2011-2020" = "skyblue"
  ))+
  theme_minimal() +
  labs(
    title = "Distance to group 1981-2000",
    x = NULL,
    y = "Bray-Curtis Distance"
  ) +
  theme(
    axis.text.x = element_text(angle = 45, hjust = 1),
    legend.position = "none"
  )


df_green <- df %>%
  filter(Group1 == "2001-2010" | Group2 == "2001-2010") %>%
  mutate(
    Compared_to = ifelse(Group1 == "2001-2010", Group2, Group1),
    Compared_to = factor(Compared_to, levels = c( "2001-2010","1940-60", "1981-2000", "2011-2020"))
  )

plot3 <- ggplot(df_green, aes(x = Compared_to, y = Distance, fill = Compared_to)) +
  geom_boxplot() +
  scale_fill_manual(values = c(
    "1940-60" = "#C6DBEF", 
    "1981-2000" = "#08519C", 
    "2001-2010" = "#3182BD",
    "2011-2020" = "skyblue"
  ))+
  theme_minimal() +
  labs(
    title = "Distance to group 2001-2010",
    x = NULL,
    y = "Bray-Curtis Distance"
  ) +
  theme(
    axis.text.x = element_text(angle = 45, hjust = 1),
    legend.position = "none"
  )


df_g <- df %>%
  filter(Group1 == "2011-2020" | Group2 == "2011-2020") %>%
  mutate(
    Compared_to = ifelse(Group1 == "2011-2020", Group2, Group1),
    Compared_to = factor(Compared_to, levels = c( "2011-2020","1940-60", "1981-2000", "2001-2010"))
  )

plot4 <- ggplot(df_g, aes(x = Compared_to, y = Distance, fill = Compared_to)) +
  geom_boxplot() +
  scale_fill_manual(values = c(
    "1940-60" = "#C6DBEF", 
    "1981-2000" = "#08519C", 
    "2001-2010" = "#3182BD",
    "2011-2020" = "skyblue"
  ))+
  theme_minimal() +
  labs(
    title = "Distance to group 2011-2020",
    x = NULL,
    y = "Bray-Curtis Distance"
  ) +
  theme(
    axis.text.x = element_text(angle = 45, hjust = 1),
    legend.position = "none"
  )

library(cowplot)
title <- ggdraw() + draw_label("Bray-Curtis distances by Year Group", fontface = 'bold', size = 14)

combined_plot <- plot_grid(plot1, plot2, plot3,plot4, nrow = 1, align = "hv", labels = c("A", "B", "C", "D"))

final_plot <- plot_grid(title, combined_plot, ncol = 1, rel_heights = c(0.1, 1))

ggsave("images/permanova/Bray_Curtis/16S/bray_permanova_Year_group.png", final_plot, width = 14, height = 6, dpi = 300)

df <- read.delim("data/16S/Beta_Diversity/bray_permanova_Plough/data/raw_data.tsv")

df <- df[df$Group1 != "unknown" & df$Group2 != "unknown", ]

df_nat <- df %>%
  filter(Group1 == "no" | Group2 == "no") %>%
  mutate(
    Compared_to = ifelse(Group1 == "no", Group2, Group1),
    Compared_to = factor(Compared_to, levels = c("no", "yes"))
  )

plot3 <- ggplot(df_nat, aes(x = Compared_to, y = Distance, fill = Compared_to)) +
  geom_boxplot() +
  scale_fill_manual(values = c(
    "no" = "#C6DBEF", 
    "yes" = "#08519C"
  )) +
  theme_minimal() +
  labs(
    title = "Distance to No",
    x = NULL,
    y = "Bray-Curtis Distance"
  ) +
  theme(
    axis.text.x = element_text(angle = 45, hjust = 1),
    legend.position = "none"
  )




df_seed <- df %>%
  filter(Group1 == "yes" | Group2 == "yes") %>%
  mutate(
    Compared_to = ifelse(Group1 == "yes", Group2, Group1),
    Compared_to = factor(Compared_to, levels = c("yes", "no"))
  )

plot1 <- ggplot(df_seed, aes(x = Compared_to, y = Distance, fill = Compared_to)) +
  geom_boxplot() +
  scale_fill_manual(values = c(
    "no" = "#C6DBEF", 
    "yes" = "#08519C"
  ))+
  theme_minimal() +
  labs(
    title = "Distance to Yes",
    x = NULL,
    y = "Bray-Curtis Distance"
  ) +
  theme(
    axis.text.x = element_text(angle = 45, hjust = 1),
    legend.position = "none"
  )



title <- ggdraw() + draw_label("Bray-Curtis distances by Plough", fontface = 'bold', size = 14)

combined_plot <- plot_grid(plot1, plot3, nrow = 1, align = "hv", labels = c("A", "B"))

final_plot <- plot_grid(title, combined_plot, ncol = 1, rel_heights = c(0.1, 1))

ggsave("images/permanova/Bray_Curtis/16S/bray_permanova_Plough.png", final_plot, width = 14, height = 6, dpi = 300)